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How The Future Works: Why your ultimate job is to be HUMAN. A…

January 7, 2020 Big Data

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How The Future Works: Why your ultimate job is to be HUMAN. A film by Fu…

Privacy, Big Data, Human Futures by Gerd Leonhard

Cedric The Entertainer’s ‘Johnson Family Vacation’ Sequel In The Works

October 22, 2019 Humor

Cedric the Entertainer will return to star and will produce with DeVon Franklin.

A sequel to the 2004 comedy Johnson Family Vacation is in the works at Fox Searchlight.

Johnson Family Celebration will pick up nearly two decades after the events of the original film, and will see the return of Cedric the Entertainer as Nate Johnson, the well-meaning patriarch of the Johnson family that embarked on an ill-fated cross-country road trip. (Family Vacation grossed $ 31 million in theaters in 2004.)

Along with DeVon Franklin and his Franklin Entertainment banner, Cedric will produce with Eric Rhone via his A Bird and A Bear Entertainment. Michael Elliot — the writer behind Like Mike and Just Wright — will pen the sequel.

Taylor Friedman will oversee for the studio. Zahra Phillips will oversee for Franklin Entertainment.

Franklin was most recently in theaters with faith-based film Breakthrough, which grossed an impressive $ 50 million at the global box office. He is repped by WME and Hansen Jacobsen.

Cedric the Entertainer and A Bird and a Bear are repped by CAA, Visions Management and Del Shaw. Elliot is repped by Jackoway Austen.

Issa Rae Launches New Label With Atlantic Titled Raedio

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The Humor Mill

PriceWaiter CEO Stephen Culp: ‘Negotiation Has Been Around Forever Because It Works’

September 25, 2019 CRM News and Info

Fledgling e-commerce company PriceWaiter aims to save customers money, time and energy by negotiating better-than-Amazon deals on top-rated products — simply, quickly and privately.

PriceWaiter’s pitch to sellers is that it can help move inventory, maintain more margin, and make MAP (minimum advertised price) moot, resulting in more efficient pricing, new sales, and new customers with virtually no acquisition cost.

Negotiation is as old as commerce because it works — it needed an upgrade, and PriceWaiter is that upgrade, the company maintains.

With hundreds of partner retailers, hundreds of thousands of users, millions of products (more every day), and hundreds of millions in offers, PriceWaiter makes buying and selling better, and free markets freer, giving both buyers and sellers a win, the company promises.

PriceWaiter CEO Stephen Culp

PriceWaiter CEO Stephen Culp is an e-commerce veteran, and business and civic entrepreneur. In addition to PriceWaiter, he cofounded Smart Furniture, Delegator, ProDiligence, and Causeway.

A former Peace Corps Volunteer, Navy Reserve Officer, and enthusiastic migrant from Silicon Valley to the Tennessee Valley, Culp completed a law degree and graduate fellowship in negotiation at Stanford.

He recently provided the E-Commerce Times with exclusive insights into his experience with PriceWaiter and his vision for the company.

E-Commerce Times: When did PriceWaiter launch? Who founded the company, and what sparked the idea?

Stephen Culp: About six years ago, a team of e-commerce, design and software veterans — Andrew Scarbrough, Matt Bain, Mike Estes and myself — realized that e-commerce had become so efficient that it was at once both wonderful and perilous, for all involved. Whatever way you looked at it — and we had experience as manufacturers, retailers and, yes, shoppers — there was plenty of wonder and peril to go around.

For manufacturers and retailers, there was the growing — and now instant — threat of comparison shopping and what you might call “virtual showrooming” — where a seller could spend a lot of money attracting a customer, delighting them, serving them, only to lose them in the click of a button to another site selling the same product for a dollar less. Furthermore, as we had experienced starting Smart Furniture, we had the constant sense that we were leaving money on the table whenever we discounted, because we had no way of really knowing what the perfect price should be.

As shoppers, we were inundated with offers, targeting and retargeting from innumerable sketchy “deal” sites, increasingly overwhelmed keeping track of seemingly random sales events which came and went like hurricanes, and aside from fully capitulating to the siren song of Amazon, it was getting harder to know who to trust, where to truly find a deal, and how to do it when you actually needed it.

Weeeellllll… irony of ironies — as we imagined what technological innovation could best leverage and harness the wonder and peril of e-commerce for all sides, there was a moment when we realized that the solution might just be the oldest idea in commerce: negotiation. Why? As it happens, I had studied negotiation as a graduate fellow at Stanford and learned that, well, negotiation has been around forever because it works. It serves to initiate a dialogue, it builds a measure of trust, and ultimately it consummates a transaction that, in the spirit of the free market, both sides are happy with.

But back to technology — we also realized that it needed an upgrade to work well in the most efficient market in history. No one wanted to bring the used car lot to the Web. We wanted the upgrade to make buying and selling better, by making negotiation fast, simple, private and ultimately ubiquitous. That upgrade became PriceWaiter.

ECT: Some customers might not want to do the research necessary to feel confident naming a price. Is PriceWaiter just not for them?

Culp: We help make it easy. First, think of the used car lot. Next, dash that memory from your brain forever. PriceWaiter does the research, curates the best opportunities, and does the negotiation for you. If you get hung up on naming an initial price or offer, in a few weeks we’ll actually [have the ability to] make suggestions for you.

We may even prenegotiate a few deals in the future, as a gateway to negotiating on our broader catalog. But in all cases, we do the hard work and your experience will be easy — even fun. Keep in mind it’s getting better every day.

ECT: Why do sellers have secret unadvertised pricing? What’s in it for them?

Culp: Keeping the negotiation private has a number of benefits. While shoppers can obviously save money with an often exclusive deal, on the flipside, retailers can also offer exclusive deals they might not want to post to the entire Web.

To take a particular example, manufacturers with MAP policies actually benefit from PriceWaiter’s private negotiations because they sell more product without significant risk of brand or price erosion, more efficiently managing the inevitable request for discounts over the phone, email, social media, etc.

Further, as I mentioned, pricing can be honed — to the benefit of buyer and seller — to the particulars of the transaction, whether it be driven by volume, availability, time or other factors.
Recall that the founders came from all of those backgrounds, so PriceWaiter’s solution is sensitive to all of them.

ECT: Can individuals or small businesses offer their wares on PriceWaiter? If so, how can they go about it?

Culp: This is one of my favorite features of PriceWaiter, as it taps into our pretty frisky underdog streak. Recall that PriceWaiter founders have started and run smaller businesses and e-commerce operations before. We KNOW how tough it is for a small retailer to compete with — or even sell on — something like Amazon. We KNOW how frustrating it is when you know you can offer better prices or service or products than the big sellers but you don’t have a billion dollar marketing budget to make it known.

If you offer legitimate and top-rated popular products, solid inventory, great service and incredible prices, a small company can sell on PW. Visit us at PriceWaiter.com.

Leveling the playing field is a part of our mission. We’re not fans of monopolistic leverage. Call it quixotic, but part of what drives us is that we want to make the free market freer, for all.

ECT: How does PriceWaiter make its profits?

Culp: PriceWaiter takes a small commission on each sale. Sellers only pay when a transaction happens. Buyers pay nothing unless they want to tip their “waiter” who helped negotiate the deal, but there is no obligation. Ultimately, we may offer things like membership and associated benefits a la Costco, AAA, etc., but not this year.

ECT: What can shoppers expect to find at PriceWaiter? I ran three searches on the site with zero results returned for each. Then I noticed the listings for each broad category numbered only in the hundreds. It seems PriceWaiter is more like an online boutique meant for browsing than a store that will have specific items that customers are seeking. What other online store is PriceWaiter like in terms of selection?

Culp: Think of a good Trader Joe’s vs. a bad Walmart. Our initial focus is on quality of deals vs. quantity of deals, based on a set of criteria that governs what products we choose to feature. It’s not perfect yet — think of an early Trader Joe’s, still experimenting — but since our goal is to save you money by negotiating better deals on top-rated products, we are constantly curating based on both the quality of the deal and the quality of the product.

Second, the site has not had its “grand opening” yet, so it is literally changing hourly, as we push improvements to selection, search, negotiation and more.

Third, as to your question about what other online store PriceWaiter is like in terms of selection, most curated shopping sites are limited to a niche or a category — e.g., fashion or gadgets — but we aim to be more than that.

ECT: How do you plan to draw customers to PriceWaiter? What will keep them coming back?

Culp:
Ultimately PriceWaiter will be wherever you shop. First, we already have the footprint — and 500,000 users — with our SaaS product on partner retailer sites; second, the PriceWaiter extension, which pops up anytime we can offer you a better deal while you shop on Amazon; and third, PriceWaiter.com, which will offer Amazon-beating and often Internet-beating prices visible on multiple channels.

And without giving too much away, we believe there’s a powerful social element here as well. We’ve been amazed at the psychological power of the “win” in shoppers’ minds.

ECT: How can PriceWaiter ensure that the sellers you work with do not traffic in counterfeit or stolen goods?

Culp: We carefully vet each retailer before any of their products even show up on the PriceWaiter site. It takes almost too much of our time, to be honest. But we’re on a first name basis with these partner sellers and dive deeply into each company’s operations, policies and products.

How does PriceWaiter compare with tools like Honey, which also helps customers get better deals on purchases?

Culp: Honey is great. And while PriceWaiter has a browser extension like Honey, PriceWaiter’s core experience includes more ways to engage, such as our marketplace website. PriceWaiter doesn’t rely on coupons, their reliability or their expiration, and simply negotiates better deals for shoppers with top retailers for top-rated products, all year-long.

ECT: As CEO, what is your vision for PriceWaiter? What place do you see the company occupying in the e-commerce landscape five years from now?

Culp: My vision would be for PriceWaiter to make buying and selling better — and free markets freer — by making negotiation fast, simple, private and — ultimately — ubiquitous. It is no accident that we’re all about negotiation. The entire world of commerce is ultimately about negotiation. We’re just going to make it better for the world of buyers and sellers.

For buyers, PriceWaiter should ultimately be your first — and last — stop when you need something. Like someone you trust who does all the shopping for you, we’ll find it for you and deliver it at a savings. For sellers, we will level the playing field. Our vision is a constructive free market in which all sides get a win.

ECT: What types of payment does PriceWaiter accept?

Culp: All major credit cards.

ECT: What is PriceWaiter’s shipping policy?

Culp: PriceWaiter shipping and returns policy mirrors our retail partners and is typically shipped within a few days, with a 30-day return policy. Custom items generally have longer lead times.

ECT: What is PriceWaiter’s returns policy?

Culp: We have a 30-day return policy on all items.

ECT: When will PriceWaiter have its official grand opening?

Culp: We’re shooting for around Oct. 15 for things to be working swimmingly for all.

Mick Brady is managing editor of ECT News Network.

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CRM Buyer

Google devises conversational AI that works better for people with ALS and accents

August 13, 2019 Big Data

Google AI researchers working with the ALS Therapy Development Institute today shared details about Project Euphonia, a speech-to-text transcription service for people with speaking impairments. They also say their approach can improve automatic speech recognition for people with non-native English accents as well.

People with amyotrophic lateral sclerosis (ALS) often have slurred speech, but existing AI systems are typically trained on voice data without any affliction or accent.

The new approach is successful primarily due to the introduction of small amounts of data that represents people with accents and ALS.

“We show that 71% of the improvement comes from only 5 minutes of training data,” according to a paper published on arXiv July 31 titled “Personalizing ASR for Dysarthric and Accented Speech with Limited Data.”

Personalized models were able to achieve 62% and 35% relative word error rate (WER) improvement for ALS and accents respectively.

The ALS speech data set consists of 36 hours of audio from 67 people with ALS, working with the ALS Therapy Development Institute.

The non-native English speaker data set is called L2 Arctic and has 20 recordings of utterances that last one hour each.

Project Euphonia also utilizes techniques from Parrotron, an AI tool for people with speech impediments introduced in July, as well as fine-tuning techniques.

Written by 12 coauthors, the work is being presented at International Speech Communication Association, or Interspeech 2019, which takes place September 15-19 in Graz, Austria.

“This paper’s approach overcomes data scarcity by beginning with a base model trained on thousands of hours of standard speech. It gets around sub-group heterogeneity by training personalized models,” the paper reads.

The research, which a Google AI blog post highlighted today, follows the introduction of Project Euphonia and other initiatives in May, such as Live Relay, a feature to make phone calls easier for deaf people, and Project Diva, an effort to make Google Assistant accessible for nonverbal people.

Google is soliciting data from people with ALS to improve its model’s accuracy and is working on next steps for Project Euphonia, such as using phoneme mistakes to reduce word error rates.

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Big Data – VentureBeat

Getting A Bot That Really Works: Best Corporate Architectures For Conversational Interfaces

June 19, 2019 SAP

People today expect “instantaneity.” That’s why messaging has become the most popular interface in the world: Billions of messages are sent every hour! But while the public has shifted to this conversational era, companies and governments are still living in the past.

Chatbot (n.): computer program or artificial intelligence that conducts a conversation via auditory or textual methods.

When brands record a drastic increase in customer support requests, they are failing to provide a good experience for their customers and are losing them. Let’s not forget that poor customer service amounts to $ 1.6 trillion annual losses in the U.S. alone.

“There are many reasons for a brand to build a bot! The two most important are innovation and customer relations. Innovation generates convictions about what you want to do with chatbots, giving you the opportunity to rethink your customer or employee relationship. All in the goal of offering a more powerful service.”
— Christophe Tricot (@ctricot), AI expert and manager at Kynapse

In a previous article, we talked about why chatbots are the only viable solution to scale customer service in major corporations. Brands are struggling to handle the booming number of customer requests and, because of bad customer care, are losing money and gaining a bad reputation. Bots, by excelling at managing simple customer conversations, are definitely the best solution: They automate support while increasing productivity and customer experience quality.

But how do you build an efficient corporate chatbot to achieve those goals?

Don’t think vertical

To get a better understanding, it helps to understand how the chatbot market has evolved in the past two years. In 2016, the global direction was that chatbots were intended to fully manage conversations, from beginning to end, without human intervention. Any chatbot unable to do so was discarded as inefficient. When working with customers, we used to identify the top five most-talked-about topics in our client’s customer support. Then, we’d work on automating them from A to Z with a chatbot. In the end, you’d have a chatbot capable of managing five vertical use cases perfectly.

“The three most common pitfalls of bot building are not having any real use case to support, not involving the right people from the beginning, or creating a chatbot disconnected from the company’s information system.”
— Christophe Tricot (@ctricot), AI expert and manager at Kynapse

But reality struck back. Even if you can manage five topics flawlessly, the majority of people using the bot will talk about something outside its scope. It doesn’t matter if the bot can quickly provide an invoice or update your contact details; if you want to know about the latest product and the bot replies, “I’m sorry I don’t know what you mean,” the experience is a failure to the user. And since the bot is discarded as an inefficient interface, the customer will not come back to use it, even if the bot could help this time.

Introducing the receptionist pattern

The receptionist is a design pattern we created that thinks horizontally and not vertically. The goal is to provide any corporation with a good customer support experience that leaves customers satisfied. No more, no less.

Therefore, a chatbot should not limit the range of topics supported. On the contrary, it should cover every area.

The receptionist is a bot design pattern that positions the bot at the beginning of every single user input. Every question passes through the bot, which is then capable of understanding what the request refers to. That’s the key: the chatbot understands every single request. However, that doesn’t mean the chatbot needs to treat everything. After understanding the question, the chatbot can either:

Handle it autonomously through a fully automated conversation

Start the conversation to gather important information (e.g., client number and email address) then hand the conversation over to a human agent

Dispatch the request to the correct service and hand it over to a human agent

Because this architecture is horizontal, any customer request is taken care of smoothly. It doesn’t matter if it is by a human or a bot, as long as the experience is smooth.

chatbot architecture 1024x616 Getting A Bot That Really Works: Best Corporate Architectures For Conversational Interfaces

But if the bot doesn’t manage things autonomously, what’s in it for companies?

We’ve discussed the return on investment of one of our customers, a major telecommunication company in France, in a previous article. By using the receptionist pattern, our client greatly improved customer support satisfaction by reducing conversation duration by half, as well as by reducing the rate of multiple transfers. The chatbot was also capable of autonomously resolving 20% of all conversations, boosting the brand’s productivity.

Another one of our customers in the telecommunications field also implemented the receptionist pattern. After only weeks in production, the chatbot’s heavy usage on both the website and mobile app reduced the rate of aborted conversations from 15% to 0%.

Aborted conversations are when a customer starts a conversation and never replies to the agent afterward, most often because of the long waiting time. These are non-issues with the receptionist pattern! First, because there is no waiting time, users are less likely to drop the conversation. Second, the chatbot does all the onboarding, so if the user doesn’t engage in the conversation, the chat will never be transferred to a human agent. Therefore, agents are not disrupted, nor do they waste time with pointless requests, and the entire company’s service quality increases along with customer satisfaction.

And it’s not just us!

“We’ve built a GDPR chatbot capable of informing users on the new rules and regulations of data protection. Users love it because they can quickly make sense of a complex law. That’s why bots are great.”
— Christophe Tricot (@ctricot), AI expert and manager at Kynapse

So whether it’s in customer service, marketing, or sales, chatbots are becoming more and more sophisticated.

We believe the receptionist pattern will be a great asset to the conversational AI step of your digital transformation. Happy bot building!

Learn more

Want to build your own conversational bot? Get started with SAP Conversational AI!

And if you have any questions about a chatbot project, please contact our team. We’d be happy to discuss it with you.

This article originally appeared on the SAP Analytics blog and is republished by permission.

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Digitalist Magazine

IF IT WORKS WITHOUT VIOLATING YOUR DATA AND PRIVACY…..

April 26, 2019 Humor

New idea for airline check-in:

Airline passengers of the future might be able to check in for flights and clear security and immigration, and get weighed – while going up an escalator for a mere minute.

That’s according to two industrial designers who’ve come up with a concept called ‘Aerochk’, a high-tech escalator bristling with all the necessary computer wizardry to complete the aforementioned checks.

They believe that the concept would slash long delays at airport security and therefore drastically cut the number of passengers who miss flights.

Aerochk has been conceived by industrial designers Ashish Thulkar from India and Canadian Charles Bombardier.

They say that when passengers arrive at an airport, rather than waiting in a separate security line, they would just walk towards the nearest Aerochk on their way to their boarding gate.

Passengers would place their passport on the left side of the machine and their luggage on the right, allowing the passport, the traveller and the luggage to be checked simultaneously.

The linear robotic passport conveyor would then check if the passport is valid and if the person is registered for an upcoming flight.

It would then register them for their flight and perform all other necessary background checks.

Facial recognition would confirm the passport photo with the individual on the Aerochk and specialized devices would confirm that the passport in question has not be tampered with or is fraudulent. In the event of a person’s denial to travel – i.e. invalid documents, failed background check – the Aerochk would set in motion a process to alert the relevant authorities.

Each traveler embarking on the Aerochk would pass through a portal where they would be identified by cameras and other sensors.

Their height and weight would be recorded to optimize the weight and balance of the aircraft and other equipment would be used to identify passengers and determine if they pose a threat to the flight or a country.

The Aerochk could even ask questions to each traveler and record their vocal answers.

The luggage conveyor would check if bags contain dangerous or prohibited items using multiple types of scanners including ‘electronic noses’.

Each suitcase would be photographed, weighed and associated with its owner automatically.

Larger bags would be diverted into the cargohold while hand baggage would be picked up by passengers upon exiting the Aerochk.

If a problem was detected on a suitcase or if more information is required, then it would be routed to a different exit and inspected by an airport agent.

The designers claim that Aerochk reduces the likelihood of human error, adding that currently it is very easy for workers in airport security to miss contraband in luggage simply due to the excessive volumes that they have to process every hour.

As it is still in the concept stage, the idea has not yet been sold to any airport but the two designers believe it could be easily installed in airports, ports and bus and railway stations around the world.

The designers say: ‘Technologies already exist to accomplish this type of fast and efficient check-in.

‘Other versions of the Aerochk system could even be designed and adapted for children, disabled people, pregnant women, and so on.

‘The optimal way to organise this new process is open for debate, but it is clear that we could all benefit from a faster and easier boarding process.’

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Google works with Aravind Eye Hospital to deploy AI that can detect eye disease

February 26, 2019 Big Data

For the better part of four years, Alphabet life sciences company Verily and Google’s AI research division have been developing an artificially intelligent (AI) system that can diagnose diabetic retinopathy (DR), a disease that can cause permanent eye damage if left untreated. (It’s the fastest-growing cause of blindness among the more than 415 million diabetic patients worldwide, according to the National Eye Institute.) Today, in an extension of their work, Google revealed that it has deployed the algorithm for real-world clinical use at Aravind Eye Hospital in Madurai, India.

Google detailed its partnership with Aravind in 2017, at Wired’s Business Conference and the annual TensorFlow Developer Summit. The hospital’s been working on an automated diabetic retinopathy screening since 2003, but according to Dr. R. Kim, chief medical officer and chief of retina services, Google’s AI-driven approach far surpassed early efforts in terms of both speed and accuracy.

Thanks to the algorithm — which recently received a CE mark, indicating it meets the European Union Directive’s standards for medical devices — Kim said physicians at Aravind’s vision centers will have “more time to work closely with patients on treatment and management of their disease” while “increasing the volume of screenings [they] can perform.”

Developing the AI-driven DR screening approach involved curating a dataset of 128,000 ophthalmologist-evaluated images of the interiors of eyeballs, according to Google, which were used to train a deep neural network — layers of mathematical functions modeled after biological neurons — to detect DR. Its performance was tested on two separate clinical validation sets totaling around 12,000 images, and the results showed that, compared with a panel of human ophthalmologists, it met or exceeded baseline performance. (It has a 97.5 percent accuracy rate.)

Google last year said that it’s been conducting similar research in Thailand, and at the AI for Social Good Summit in Bangkok announced a partnership with the Rajavithi Hospital to pilot its DR-screening algorithm.

The Mountain View company has invested broadly in AI health care applications. Last spring, its Medical Brain team claimed to have created an AI system that could predict the likelihood of hospital readmission and to have used it to forecast mortality rates at two hospitals with 90 percent accuracy. In February 2018, scientists from Google and Verily created a neural network that could accurately deduce basic information about a person, including their age and blood pressure, and whether they were at risk of suffering a major cardiac event like a heart attack. And more recently, Google said it had developed AI that could detect metastatic breast cancer with 99 percent accuracy.

DeepMind, Google’s London-based AI research division, is involved in several health-related AI projects, including an ongoing trial at the U.S. Department of Veterans Affairs that seeks to predict when patients’ conditions will deteriorate during a hospital stay. Previously, it partnered with the U.K.”s National Health Service to develop an algorithm that could search for early signs of blindness. And in a paper presented at the Medical Image Computing & Computer Assisted Intervention conference earlier this year, DeepMind researchers said they’d developed an AI system capable of segmenting CT scans with “near-human performance.”

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Big Data – VentureBeat

How Business Partnering Will Change The Way Finance Works

February 14, 2019 SAP

Part 2 in a 2-part series. Read Part 1.

The finance function is transforming, and some would say it’s standing on a burning platform. Automation and artificial intelligence will eliminate jobs, and a large part of the workforce will need retraining. During such transformative times, it’s important though to keep an eye on what must stay the same, because not everything is changing. The finance function must still perform its responsibilities and generic roles in the company.

Do more with less – and do it better

The transformation is not about changing the role of finance. That remains as it has always been. The change is that we must do more with less and do the things we’re already doing (or were supposed to do, but didn’t have the time) better. Most of us are well aware that the cost of finance must go down. In fact, that’s been the backbone of the transformation for years, with outsourcing and offshoring being the prime tools. What’s new is that instead of a pure cost focus, we will start to think more about the value of finance. How can each of us impact value creation?

The answer is business partnering! Business partnering can be applied in each of the three generic roles of the finance function, which can be defined as compliance, control, and advisory. This is a crucial point, because even though some companies have specific roles titled “Finance Business Partner,” the act of business partnering can be done by all roles in the finance function, from the billing clerk to the CFO.

Business partnering will help you refocus your work to start doing the right things (as opposed to just doing things right). The right things could be, for example:

Ensuring that legal requirements are implemented only according to standards and not over-implemented at additional cost (compliance).

Ensuring an efficient budget process that facilitates the right discussions about future business activities – instead of a lengthy process that no one values and that produces numbers that are outdated even before the budget is finalized (control).

Using analysis to identify insights that will help your stakeholders make better business decisions, which you influence through skillful communication and problem solving (advisory).

All of this will ensure that you do more with less, and there’s not even any magic to it!

Business partnering is a game changer

Business partnering is for everyone and has the potential to change the game for how finance interacts with the rest of the company and impacts value creation. However, it requires new competencies that don’t come naturally to many finance professionals. Therefore, to realize the potential, we must focus on developing the people working in the function by changing their mindset. Instead of always thinking of the cost of finance, we must consider the value of finance. Through this mindset change, we can transform the finance function from a cost center to a profit center.

We know it’s a long journey to fully implement the concept and train your people on the competencies required to succeed with business partnering. That’s why, together with my colleagues Bo Foged and Henriette Fynsk, we have written a book, “Create Value as a Finance Business Partner – Transforming the Finance Function into a Profit Center,” that covers the why, what, and how of business partnering. It describes important considerations to make at each step of the implementation journey, coupled with examples we have personally seen of how business partnering can be implemented properly. The book is the catalyst for changing how we work in finance.

For more on building a stronger finance operation, see Many CFOs Don’t Have A Succession Plan. That’s A Big Problem.

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Digitalist Magazine

CNN Refuses To Use San Diego News Station Which Says The Wall Works

January 11, 2019 Humor

CNN only wants to use news outlets which will agree with the false narrative they want to push on the America Public.

As part of their coverage of the border fence debate, CNN decided to reach out to San Diego’s KUSI-TV to ask what locals think about the barrier separating their little chunk of America from Mexico.

The end result was this 40-second segment posted Thursday detailing exactly what happened.

“A sign of the times in this debate on the shutdown,” anchor Anna Laurel says. “CNN asked if KUSI would provide a reporter to offer our local view of the debate, especially to learn if the wall works in San Diego.”

KUSI is an independent local news station in California. CNN probably expected someone to come on and tell them how the wall was a crime against humanity and it was a waste of money.

They weren’t going to get that.

“KUSI offered our own Dan Plante, who’s reported many times that the wall is not an issue here,” anchor Sandra Maas said.

“In fact, most officials believe that it is effective. The issue we face is the migrants and the debate over their treatment.”

This would have been an interesting segment — Plante, certainly not offering a take that CNN wasn’t used to, spurring some conversation on a network that’s not necessarily known to view the wall with any great kindness.

I say, of course, “would have been.” It didn’t happen for reasons that aren’t going to shock you.

“Now, knowing this, CNN declined to have us on our programs,” Laurel says, “which often present the wall as not required in other places like the stretch of the Texas border that the president visited earlier today.

“They didn’t like what they heard from us,” Laurel concludes.

“Just some background for you,” Maas says.

Video at the Link.

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Google’s Duplex is rolling out to Pixel owners — here’s how it works

November 22, 2018 Big Data

Google Duplex-powered calls have finally arrived. Sort of. For some people.

A spokesperson confirmed to VentureBeat that Duplex — Google’s artificially intelligent chat agent that can arrange appointments over the phone — has expanded from a “set of trusted tester users” earlier this year to a “small group” of Google Pixel phone owners, who can now use Duplex via the Google Assistant to secure restaurant reservations in “select cities.”

Presumably, “select cities” refers to the previously announced pilot metros of New York, Atlanta, Phoenix, and San Francisco. If you’re not in the “trusted tester” group, you’ll likely get an error along the lines of “Sorry, I can’t call to make reservations for you yet, but here’s their phone number: [10 digits].”

To be clear, it’s not quite the Duplex experience Google demoed at its I/O 2018 developers conference in May — Google Assistant isn’t booking haircut appointments just yet, and it can only place calls in English. But importantly, it’s no longer limited to businesses with which Google has explicitly partnered.

“We’re currently ramping up the ability to book restaurant reservations through the Google Assistant over the phone using Duplex technology,” the spokesperson told VentureBeat. “To help deliver a good experience to Pixel users and to businesses, we’re starting with a slow rollout … and will expand to more Pixel users as we continue to ramp up.”

Google isn’t provisioning Duplex access to members of the press — we asked. But as luck would have it, our Pixel 3 and a Pixel 3 XL review units made it into the initial wave. So naturally, we put Duplex to the test.

Booking a table with Duplex

The most reliable way to book a table using the Google Assistant is by saying “Hey Google, make a restaurant reservation” or “Hey Google, reserve a table,” optionally appended with “in [a neighborhood or borough].” For example: “Make a restaurant reservation in Manhattan.”

Google’s Duplex is rolling out to Pixel owners — here’s how it works

Above: Restaurant results in the Google Assistant. Note the “Request a table there” button in the bottom-left corner.

Those utterances spring up a list of options that can be refined by cuisine (e.g., Thai, Chinese, barbecue, American). Selecting a restaurant — either by saying its name or by tapping on it — brings you to the next step in the Duplex-powered reservation flow. Alternatively, you can look up a specific restaurant first, and if the option shows up, tap “Request a table there.”

Above: If you’re lucky, there will be an option to “request a table.”

Duplex doesn’t yet work with every restaurant. For some spots we tried to reserve — even those with public phone numbers — Google Assistant threw this error message: “Unfortunately, that restaurant only takes reservations online. So you’ll have to book with them directly.” In other cases, it told us that it “[couldn’t] make reservations at [the] particular restaurant.”

Google has previously said that businesses will be able to opt out from receiving calls by toggling a setting in their Google My Business account. That might have something to do with the roadblocks we encountered, but it just as easily might be early day jitters. We’ve reached out to Google for clarification.

For restaurants that haven’t been delisted, kicking off a reservation is a relatively straightforward process. Google Assistant first prompts you to specify the size of your party, suggesting sizes like two, three, or four people. The maximum is 10 — exceed it, and the Assistant curtly cuts off the exchange with a message indicating it can’t make reservations for large parties yet.

After you’ve communicated the size of your table, confirming a date comes next. Google Assistant suggests up to seven days out, but it will just as readily facilitate a request for several weeks — or even months — in advance. Years are a different story — Google Assistant foiled our attempt to book a table in 2021.

Once you’ve settled on a date, you’ll be asked to supply a preferred time within the restaurant’s hours of operation, in addition to a backup time window (for instance, 6:00 p.m to 7:00 p.m.) in the event the requested time is not available.

Above: The Google Assistant won’t attempt to make a reservation during store hours.

At this stage, Google Assistant asks for a booking phone number, which by default is your phone number. You can supply a new one, or alternatively tap the Manage Phone Number button at the bottom of the screen to pull up the Phone settings page on the Google Account dashboard. It’s populated with numbers you’ve provided and verified for Google services like Hangouts and Google Voice, which you can edit and delete at your leisure.

Finally, after you’ve given a phone number, Google Assistant asks you to confirm the details — the place, date, and time. Then it’s off to the races.

Managing Duplex reservations

It’s at this final screen where you’ll find the My Reservations button. Select it, and it will surface an inline list of reservations automatically imported from Gmail, manually added to Google Calendar, or placed with Duplex. Duplex-facilitated reservations that haven’t been confirmed bear a blue “Pending” tag underneath the name of the restaurant and a View details link.

Select that link, and the Google Assistant serves a webpage with a confirmation number and a chronological list of attempts that have been made to book your reservation; a reservation summary with the date, time, party size, restaurant name, and restaurant address; and the name and phone number associated with the reservation.

What if you have to cancel a reservation? Easy — tap the Cancel button at the bottom of the screen, and Google Assistant places a call to inform the restaurant. Perhaps anticipating abuse, Google has imposed a hard limit of one cancellation per restaurant per day. If you cancel a reservation somewhere, you won’t be able to rebook for 12 to 24 hours. And if you cancel too many reservations in a row, you’ll be temporarily prevented from using Duplex altogether.

Above: The summary screen confirming the reservation.

One interesting item of note: Duplex is definitely a Pixel-only affair for now. We tried to get the Google Assistant to place a reservation from a Google Smart Display (the LG Xboom WK9), but got this response: “I’m sorry, I can’t make reservations … from this device yet.” We might be reading too much into it, but that reply suggests that Smart Displays will eventually be able to tap Duplex for reservations and appointments. Presumably, Google’s not rushing into this.

The Duplex call experience

Booking restaurants with a robot would be fraught with peril, you’d think, considering the number of things that might go wrong. What if the human on the other end has a thick accent that throws off Duplex’s speech recognition? What if they ask an obscure question the system hasn’t been trained to handle? Or what if the restaurant’s listed number is no longer in service?

Google revealed earlier this summer that Duplex is able to complete four out of five fully automated tasks. That sounds about right — every time Duplex allowed us to make a restaurant reservation, it completed the task successfully.

One restaurant, Cafe Prague in San Francisco, even let us film the experience from their point of view (apologies for the portrait view):

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Notice that Duplex begins the conversation by saying “Hi, I’m calling to make a reservation for a client. I’m calling from Google, so the call may be recorded.”

Google received a ton of criticism after its initial Duplex demo in May — many were not amused that Google Assistant mimicked a human so well. In June, the company promised that Google Assistant using Duplex would first introduce itself.

Part of the reason Duplex sounds so natural is because it taps Google’s sophisticated WaveNet audio processing neural network, and because it intelligently inserts “speech disfluencies” — the “ums” and “ahs” people make involuntarily in the course of conversation. They come from a branch of linguistics known as pragmatics, which deals with language in use and the contexts in which it is used — including such things as taking turns in conversation, text organization, and presupposition.

Vice president of engineering for the Google Assistant Scott Huffman revealed in interviews this summer that the disfluencies turned out to be the key to advancing talks in tests of Duplex. Without them, he said, people were more likely to hang up as the exchange starts to feel overly artificial.

They have another, more practical purpose: buying time. When Duplex is confronted with an uncertain response from a conversation partner after, say, requesting a table for three, it’ll reiterate with a disfluency — “ah, for three.”

Of course, restaurant owners don’t have to speak with the Google Assistant if they decide they’d rather not. At the beginning of exchanges, Duplex makes clear that the call is automated. In states with two-party consent laws (California, Connecticut, Florida, Illinois, Maryland, Massachusetts, Montana, New Hampshire, Pennsylvania, and Washington), it informs the person on the other end that they’re being recorded. If they respond with “I don’t want to be recorded” or some variation of the phrase, the call is handed off to a human operator on an unrecorded line. (Those operators also annotate the call transcripts used to train Duplex’s algorithms.)

Those precautions are unlikely to put to rest the ethical and legal concerns raised by Duplex’s debut. But as Google steadily marches toward its goal of launching Duplex in new U.S. cities in states, they’ll be a small comfort for businesses that opt to field its autonomous phone calls.

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